End-to-end secure data retrieval in a dispersed storage network

ABSTRACT

A method includes a first computing device retrieving a decode threshold number of encrypted encoded data slices. The method further includes the first computing device generating a decoding matrix based on pillar numbers of the decode threshold number of encrypted encoded data slices and an encoding matrix. The method further includes the first computing device dispersed storage error decoding the decode threshold number of encrypted encoded data slices based on the decoding matrix to produce an encrypted data segment. The method further includes the first computing device sending the encrypted data segment and the pillar numbers to a second computing device. The method further includes the second computing device identifying a particular subset of encryption keys of the set of encryption keys based on the pillar numbers. The method further includes the second computing device decrypting the encrypted data segment based on the particular subset of encryption keys.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 62/222,819,entitled “IDENTIFYING AN ENCODED DATA SLICE FOR REBUILDING”, filed Sep.24, 2015, which is hereby incorporated herein by reference in itsentirety and made part of the present U.S. Utility Patent Applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Security of a cloud storage system is an important aspect for commercialviability. Security of any system, including cloud storage systems, ismost vulnerable when data is in its raw form (e.g., no encryption, nopassword protection, etc.). When data is in its raw form, a person ofill-intent only needs to gain access to a computer storing, processing,and/or transmitting the data to have unauthorized access to the data. Inmany cloud storage systems, when data is being processed for dispersedstorage, it is done so in a raw data format.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a computingdevice securely retrieving a data segment from storage units via anothercomputing device in accordance with the present invention;

FIG. 10 is a diagram of an example of encrypting an encoded data slicein accordance with the present invention;

FIG. 11 is a diagram of an example of generating a decoding matrix froman encoding matrix in accordance with the present invention;

FIG. 12 is a diagram of an example of decoding a received encrypted andcoded matrix in accordance with the present invention;

FIG. 13 is a diagram of an example of decrypting an encrypted recovereddata matrix in accordance with the present invention;

FIG. 14 is a schematic block diagram of an embodiment of a computingdevice securely retrieving a data segment from storage units via anothercomputing device in accordance with the present invention; and

FIG. 15 is a logic diagram of an example of a method of end-to-endsecure data retrieval in a DSN in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12 -16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 and 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data (e.g., data 40) as subsequently described withreference to one or more of FIGS. 3-8. In this example embodiment,computing device 16 functions as a dispersed storage processing agentfor computing device 14. In this role, computing device 16 dispersedstorage error encodes and decodes data on behalf of computing device 14.With the use of dispersed storage error encoding and decoding, the DSN10 is tolerant of a significant number of storage unit failures (thenumber of failures is based on parameters of the dispersed storage errorencoding function) without loss of data and without the need for aredundant or backup copies of the data. Further, the DSN 10 stores datafor an indefinite period of time without data loss and in a securemanner (e.g., the system is very resistant to unauthorized attempts ataccessing the data).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The managing unit 18 creates and stores user profile information (e.g.,an access control list (ACL)) in local memory and/or within memory ofthe DSN memory 22. The user profile information includes authenticationinformation, permissions, and/or the security parameters. The securityparameters may include encryption/decryption scheme, one or moreencryption keys, key generation scheme, and/or data encoding/decodingscheme.

The managing unit 18 creates billing information for a particular user,a user group, a vault access, public vault access, etc. For instance,the managing unit 18 tracks the number of times a user accesses anon-public vault and/or public vaults, which can be used to generate aper-access billing information. In another instance, the managing unit18 tracks the amount of data stored and/or retrieved by a user deviceand/or a user group, which can be used to generate a per-data-amountbilling information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one 10 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment (i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of

FIG. 4. In this example, the computing device 12 or 16 retrieves fromthe storage units at least the decode threshold number of encoded dataslices per data segment. As a specific example, the computing deviceretrieves a read threshold number of encoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of an embodiment of a computingdevice 14 securely retrieving a data segment (e.g., data segment 1) fromstorage units (e.g., SU #1 through SU #5) via another computing device16. Computing device 16 includes the DS client module 34, whichprocesses the encoding of data segments into sets of encoded data slicesand the decoding of decode threshold number of sets of encoded dataslices into data segments as discussed with reference to one or more ofFIGS. 1-8. To facilitate end-to-end secure retrieval of data, thestorage units SU #1 through SU #5 and the computing device 14 (whichdoes not include a DS client module or is not currently using it for adata retrieval) share one or more sets of encryption keys that are notshared with computing device 16. As such, computing device 16 isencoding and decoding encrypted data segments without the ability toconvert them into a raw data format.

In an example, the computing device 14 sends a data retrieval request tocomputing device 16 regarding a set of encoded data slices (e.g., EDS1_1 through ED 5_1), which correspond to data segment (e.g., datasegment 1). Computing device 16 sends a set of EDS retrieval requests tothe set of storage units (SU #1 through SU #5). In this example, SU #1,SU #, and SU #4 respond to provide a decode threshold number of encodeddata slices.

Prior to sending its respective encoded data slice (EDS) to computingdevice 16, each storage unit (e.g., SU #1, SU #, and SU #4) encrypts itsEDS with a unique key to produce encrypted encoded data slices. Forexample, SU #1 encrypts EDS 1_1 with key 1, SU #3 encrypts EDS 3_1 withkey 3, and SU #4 encrypts EDS 4_1 with key 4.

As a specific example and with reference to FIG. 10, a storage unit(e.g., SU #1) converts the encryption key (e.g., key 1) into a keystream. The encryption key may be any alpha-numeric value shared by thestorage unit and computing device 14. As such, the encryption key may bea word, a specific number, a randomly generated number, etc. The storageunit converts the key into a key stream (e.g., key 1 into key stream 1).For example, if the encryption module 81 performs a finite fieldaddition on the key stream (e.g., key stream 1) and the encoded dataslice (e.g., EDS 1_1) to produce the encrypted data slice (e.g.,encrypted EDS 1_1), the storage unit expands, contracts, and/orotherwise modifies the key to produce the key stream such that the keysteam has a substantially similar number of bits as the encoded dataslice. For example, the storage unit generates the key steam by paddingthe key, repeating the key, performing one or more mathematicalfunctions on the key, performing one or more logic functions on the key,performing a compression function on the key, and/or performing anexpansion function on the key.

The encryption module 81 (e.g., a finite field adder) encrypts theencoded data slice based on the key stream to produce the encryptedencoded data slice. In one embodiment, the finite field addition is doneusing an exclusive OR function. After encryption, each storage unitsends its encrypted encoded data slices to computing device 16.

Returning to the discussion of FIG. 9, computing device 16, while nothave access to the encryption keys, is aware that the encoded dataslices are encrypted. With this knowledge, computing device 16 decodesthe decode the decode threshold number of encrypted encoded data slices(e.g., encrypted EDSs 1_1, 3_1, and 4_1) to produce an encrypted datasegment 80. For example, and as shown in FIGS. 11 and 12, computingdevice 16 converts the encoding matrix 82 into a decoding matrix 84based on the pillar numbers (PN) of the encoded data slices it receives.In this example, computing device 16 receives encrypted EDSs 1_1, 3_1,and 4_1, which corresponds to pillar numbers 1, 3, and 4. Accordingly,rows 1, 3, and 4 of the encoding matrix 82 are used to create thedecoding matrix 84.

Computing device 16 the decodes the decode threshold number of encryptedencoded data slices (e.g., encrypted EDSs 1_1, 3_1, and 4_1), whichforms a received coded matrix 86, based on the decoding matrix 84 toproduce an encrypted recovered data matrix 88. As shown for thisexample, the encrypted recovered data matrix 88 includes three rows ofencrypted data blocks. For example, the first row includes data blocksD1-D4, which are encrypted based on an encryption function and anencryption key (as discussed with reference to FIG. 10).

Returning to the discussion of FIG. 9, computing device 16 sends a listof the pillar numbers (e.g., PN 1, PN 3, and PN 4 in this example) andthe encrypted data segment 84, which corresponds to the encryptedrecovered data matrix 88. Based on the pillar numbers, computing device14 selects the appropriate keys to decrypt the encrypted data segment 84to recover the data segment (e.g., data segment 1).

FIG. 13 is a diagram of an example of decrypting an encrypted recovereddata matrix 88 by computing device 14. As shown, computing device 14receives the list of pillar numbers (PN) and the encrypted recovereddata matrix 88 (i.e., the encrypted data segment). In an embodiment,computing device 14 generates a subset of key streams from theparticular subset of encryption keys. For example, generates key stream1 from key 1; key stream 3 from key 3; and key stream 4 from key 4 asdiscussed with reference to FIG. 10. Computing device 14 decrypts, viadecryption module 14, the encrypted recovered data matrix 88 using thekey steams.

As a specific example, the decryption module 90 performs a finite fieldaddition (which, in one embodiment is an exclusive OR function) of keysteam 1 with the first row of the encrypted recovered data matrix 88(e.g., encrypted function ({D1, D2, D3, D4}, key) to recover anunencrypted row of the data matrix 92 (e.g., D1, D2, D3, and D4). Asimilar function is done to recover the other two rows of the datamatrix (e.g., D5-D8 and D9-D12). The computing device converts the datamatrix 92 into the data segment.

FIG. 14 is a schematic block diagram of an embodiment of a computingdevice securely retrieving a data segment from storage units via anothercomputing device. This embodiment is similar to the embodiment of FIG.9, with the exception that more than one set of encryption keys may beused to encrypt encoded data slices. For example, each set of encodeddata slices may have its own set of encryption keys. As another example,a set of encryption keys is used to encrypt sets of encoded data slicesfrom a data object, for a group of data objects, and/or for datapartitions of a data object, where a data partition includes two or moredata segments. Note that the storage units and computing device 14 eachstore the set of encryption keys.

FIG. 15 is a logic diagram of an example of a method of end-to-endsecure data retrieval in a DSN. The method begins at step 100 where afirst computing device (e.g., computing device 16) retrieves a decodethreshold number of encrypted encoded data slices from at least somestorage units of a set storage units. For example, the first computingdevice receives, at step 112 a data retrieval request for a set ofencoded data slices from a second computing device (e.g., computingdevice 14). The first computing device sends, at step 114, a set of dataretrieval requests to the set of storage units regarding the set ofencoded data slices. The storage units that respond, encrypt theirrespective encoded data slices based on respective encryption keys asdiscussed above and send a decode threshold number of encrypted encodeddata slices to the first computing device at step 116.

The method continues at step 102 where the first computing devicegenerates a decoding matrix based on pillar numbers of the decodethreshold number of encrypted encoded data slice and an encoding matrix.An example of this was discussed with reference to FIG. 11. The methodcontinues at step 104 where the first computing device dispersed storageerror decodes the decode threshold number of encrypted encoded dataslices based on the decoding matrix to produce an encrypted datasegment. An example of this was discussed with reference to FIG. 12. Themethod continues at step 106 where first computing device sends theencrypted data segment and the pillar numbers to a second computingdevice.

The method continues at step 108 where the second computing deviceidentifies a particular subset of encryption keys of the set ofencryption keys based on the pillar numbers. The method continues atstep 110 where the second computing device decrypts the encrypted datasegment based on the particular subset of encryption keys. An example ofsteps 108 and 110 was discussed with reference to FIG. 13.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for secure data retrieval in a dispersedstorage network (DSN), the method comprises: retrieving, by a firstcomputing device of the DSN, a decode threshold number of encryptedencoded data slices of a set of encrypted encoded data slices from atleast some storage units of a set storage units of the DSN, wherein theset of storage units encrypt a set of encoded data slices using a set ofencryption keys to produce the set of encrypted encoded data slices, andwherein a first encoded data slice of the set of encoded data slices isencrypted based on a first encryption key of the set of encryption keysto produce a first encrypted encoded data slice of the set of encryptedencoded data slices; generating, by the first computing device, adecoding matrix based on pillar numbers of the decode threshold numberof encrypted encoded data slices and an encoding matrix; dispersedstorage error decoding, by the first computing device, the decodethreshold number of encrypted encoded data slices based on the decodingmatrix to produce an encrypted data segment; sending, by the firstcomputing device, the encrypted data segment and the pillar numbers to asecond computing device of the DSN; identifying, by the second computingdevice, a particular subset of encryption keys of the set of encryptionkeys based on the pillar numbers; and decrypting, by the secondcomputing device, the encrypted data segment based on the particularsubset of encryption keys.
 2. The method of claim 1, wherein theretrieving the decode threshold number of encrypted encoded data slicescomprises: receiving, by the first computing device, a data retrievalrequest for the set of encoded data slices from the second computingdevice; sending, by the first computing device, a set of data retrievalrequests to the set of storage units regarding the set of encoded dataslices; and receiving, by the first computing device, the decodethreshold number of encrypted encoded data slices from the at least someof the storage units.
 3. The method of claim 1, wherein the generatingthe decoding matrix comprises: determining the pillar numbers of encodeddata slices of the decode threshold number of encrypted encoded dataslices; and reducing the encoding matrix to include rows correspondingto the pillar numbers to produce the decoding matrix.
 4. The method ofclaim 1 further comprises: generating a first key stream from the firstencryption key; and finite field adding the first key stream with thefirst encoded data slices to produce the first encrypted encoded dataslice.
 5. The method of claim 4, wherein the finite field addingcomprises: exclusive ORing the first key stream with the first encodeddata slices to produce the first encrypted encoded data slice.
 6. Themethod of claim 1, wherein the identifying the particular subset ofencryption keys comprises: generating the decoding matrix based on thepillar numbers; and determining the particular subset of encryption keysbased on rows of the decoding matrix.
 7. The method of claim 1, whereinthe decrypting the encrypted data segment based on the particular subsetof encryption keys further comprises: generating a subset of key streamsfrom the particular subset of encryption keys; converting the encrypteddata segment into an encrypted data matrix in accordance with thedecoding matrix; a finite field adding the subset of key streams withrows of the encrypted data matrix to produce a data matrix; andconverting the data matrix into the encrypted data segment.
 8. Acomputer readable memory comprises: a first memory element that storesoperational instructions, which, when executed by a first computingdevice of a dispersed storage network (DSN), causes the first computingdevice to: retrieve a decode threshold number of encrypted encoded dataslices of a set of encrypted encoded data slices from at least somestorage units of a set storage units of the DSN, wherein the set ofstorage units encrypt a set of encoded data slices using a set ofencryption keys to produce the set of encrypted encoded data slices, andwherein a first encoded data slice of the set of encoded data slices isencrypted based on a first encryption key of the set of encryption keysto produce a first encrypted encoded data slice of the set of encryptedencoded data slices; generate a decoding matrix based on pillar numbersof the decode threshold number of encrypted encoded data slices and anencoding matrix; dispersed storage error decode the decode thresholdnumber of encrypted encoded data slices based on the decoding matrix toproduce an encrypted data segment; send the encrypted data segment andthe pillar numbers to a second computing device of the DSN; and a secondmemory element that stores operational instructions, which, whenexecuted by the second computing device, causes the second computingdevice to: identify a particular subset of encryption keys of the set ofencryption keys based on the pillar numbers; and decrypt the encrypteddata segment based on the particular subset of encryption keys.
 9. Thecomputer readable memory of claim 8, wherein the first memory elementfurther stores operational instructions, which, when executed by thefirst computing device, causes the first computing device to retrievethe decode threshold number of encrypted encoded data slices by:receiving a data retrieval request for the set of encoded data slicesfrom the second computing device; sending a set of data retrievalrequests to the set of storage units regarding the set of encoded dataslices; and receiving the decode threshold number of encrypted encodeddata slices from the at least some of the storage units.
 10. Thecomputer readable memory of claim 8, wherein the first memory elementfurther stores operational instructions, which, when executed by thefirst computing device, causes the first computing device to generatethe decoding matrix by: determining the pillar numbers of encoded dataslices of the decode threshold number of encrypted encoded data slices;and reducing the encoding matrix to include rows corresponding to thepillar numbers to produce the decoding matrix.
 11. The computer readablememory of claim 8 further comprises: a third memory element that storesoperational instructions, which, when executed by a first storage unitof the set of storage units, causes the first storage unit to: generatea first key stream from the first encryption key; and finite field addthe first key stream with the first encoded data slices to produce thefirst encrypted encoded data slice.
 12. The computer readable memory ofclaim 11, wherein the third memory element further stores operationalinstructions, which, when executed by a first storage unit of the set ofstorage units, causes the first storage unit to finite field adding by:exclusive ORing the first key stream with the first encoded data slicesto produce the first encrypted encoded data slice.
 13. The computerreadable memory of claim 8, wherein the second memory element furtherstores operational instructions, which, when executed by the secondcomputing device, causes the second computing device to identifying theparticular subset of encryption keys by: generating the decoding matrixbased on the pillar numbers; and determining the particular subset ofencryption keys based on rows of the decoding matrix.
 14. The computerreadable memory of claim 8, wherein the second memory element furtherstores operational instructions, which, when executed by the secondcomputing device, causes the second computing device to decrypt theencrypted data segment based on the particular subset of encryption keysfurther by: generating a subset of key streams from the particularsubset of encryption keys; converting the encrypted data segment into anencrypted data matrix in accordance with the decoding matrix; a finitefield adding the subset of key streams with rows of the encrypted datamatrix to produce a data matrix; and converting the data matrix into theencrypted data segment.